Generally speaking, wind turbines used for power generation convert the kinetic energy of wind into electrical energy. Due to the growing need for alternative sources of energy that do not rely on fossil fuels, wind turbines are increasingly used for providing energy into the electrical grid. Wind turbines used for electrical power generation typically include a rotor with a plurality of blades (typically three) attached to a nacelle located at the top of a tower, and coupled to a generator that converts the rotational energy of the rotor into electrical energy.
Wind turbines manufacturers, designers and operators are constantly seeking new technical features and operating settings that may improve turbine performance as even small changes in performance can have a non negligible impact on the annual energy production (AEP) of a turbine. However, monitoring the impact of a potential improvement that may be small on a limited time scale but might prove significant in terms of AEP is non-trivial especially in the context of uncertainty in measurements such as e.g. power output or wind speed and dependence of performance on ambient conditions.
In order to determine whether any potential improvement to a wind turbine results in significant AEP increases, a common approach is the “side by side” method, which involves the use of two wind turbines standing side by side in a wind sector. In particular, the method typically involves monitoring two identical turbines during a reference time period, typically counted in weeks or months. Then, the improvement to be tested is implemented on one of the turbines, and the turbines are again monitored during a test period of similar length. At the end of the test period, the difference in measured power output between the turbine undergoing the test is compared to the difference in measured power output of the reference turbine during the same period in order to determine whether there is an actual difference in power output due to the implementation of the test setting(s). As stated above, such methods aim to control for uncertainty in any measurements relied upon (e.g. wind speed, power output, etc.) as well as differences in ambient conditions that may be highly variable both from site to site and over time. However, such approaches are highly time and resources consuming since two suitable turbines must be made available for testing purposes for months at a time, with longer time periods required to detect smaller improvements. Additionally, there is still uncertainty as to the effect of a potential improvement in many cases due to the high number of variable parameters and uncertain estimates, which can result in an inability to confidently identify small improvements in particular, within a reasonable time frame.
Document EP 1959130 A2 discloses a method for optimising the operation of a wind turbine based on establishing a relation between a measured response variable (e.g. power output) and a control parameter (e.g. pitch angle), taking into account one or more ambient condition measured variable. The approach intends to adjust controller settings taking into account ambient conditions.
Accordingly, there is a need for new methods to assess settings of a turbine in use, preferably without requiring a control or knowledge of the ambient conditions, and to identify parameters that impact the performance of a wind turbine, in particular where the impact may be small on a limited time scale such that long testing periods would typically be required.